Research Article
Implementation Of The Double Exponential Smoothing Method In Determining The Planting Time In Strawberry Plantations
@INPROCEEDINGS{10.4108/eai.16-11-2022.2326144, author={Fadly Shabir and Ahmad Irfan Abdullah and Sitti Alifah Amilhusna Nur}, title={Implementation Of The Double Exponential Smoothing Method In Determining The Planting Time In Strawberry Plantations}, proceedings={Proceedings of the First Jakarta International Conference on Multidisciplinary Studies Towards Creative Industries, JICOMS 2022, 16 November 2022, Jakarta, Indonesia}, publisher={EAI}, proceedings_a={JICOMS}, year={2022}, month={12}, keywords={prediction; strawberry; double exponential smoothing mape}, doi={10.4108/eai.16-11-2022.2326144} }- Fadly Shabir
Ahmad Irfan Abdullah
Sitti Alifah Amilhusna Nur
Year: 2022
Implementation Of The Double Exponential Smoothing Method In Determining The Planting Time In Strawberry Plantations
JICOMS
EAI
DOI: 10.4108/eai.16-11-2022.2326144
Abstract
Strawberry is one of the important fruit commodities and is widely grown for some people in Bantaeng district to meet market demand. High rainfall is a challenge in strawberry due to climate and time dynamics, rainfall along with climate change, not only c auses changes in the amount of rainfall but also causes a shift in the beginning of the rainy season and the beginning of the dry season. so often in the cultivation of plants such as strawberries it is difficult to adjust even too late to anticipate sudde n and extreme changes in rainfall. The stages of this research began with collecting data obtained from observation, interviews and documentation. The research design used is UML which is designed in a structured manner consisting of use case diagrams, a ctivity diagrams, sequence diagrams and class diagrams.software used in building this system is PHP and MySql for database processing. The algorithm used is Double exponential smoothing to predict rainfall, air temperature, and monthly wind speed for the n ext year using past data. The results of this study are that the system is able to provide recommendations for planting periods based on the prediction results of rainfall, air temperature, and wind speed based website. Based on the results of calculating the accuracy between the prediction results and actual data using the Mean Absolute Percentage Error (MAPE) , each has a forecasting error value of 30.69% for rainfall, air temperature 0.63%, wind speed 5.89%.